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Fog computing is considered to be an effective method to solve the problem of high latency and high energy consumption of IoT devices. A suitable computation offloading strategy can provide a low offloading cost to the user device. Most researches on computation offloading in fog computing focus on one or two targets to improve system performance, however, the actual system needs to meet a comprehensive demand. Therefore, the joint optimization of multi-objective in multiple scenarios is a very meaningful problem. Inspired by this, the paper highlights the joint optimization research for fog computing, which proposes a Joint Computation offloading, Data compression, Energy harvesting, and Application scenarios (JCDEA) algorithm. The related mathematical model is constructed and the cost expressions of local computing, fog computing, and cloud computing are derived. Through the proposed algorithm, solving the computation offloading strategy is transformed into solving the minimum cost and is simplified by controlling strategy factors. Moreover, five simulation experiments are conducted and the meaningful conclusions are drawn, which contain that (1) the cost of fog computing is lower than that of local and cloud computing in most time slots and cloud computing can compensate for fog computing in complex environments; (2) the cost increases approximately linear with the amount of offloaded data; (3) the number of user devices and the compression ratio affect the fog-to-cloud ratio (FCR), while the FCR affects the cost; and (4) the related offloading strategy distribution and the cost are obtained for different scenarios. The JCDEA algorithm always outperforms than that of the random selection algorithm in all scenarios.

We have implemented a modified Low-Density Parity-Check (LDPC) codec algorithm in ultraviolet (UV) communication system. Simulations are conducted with measured parameters to evaluate the LDPC-based UV system performance. Moreover, LDPC (960, 480) and RS (18, 10) are implemented and experimented via a non-line-of-sight (NLOS) UV test bed. The experimental results are in agreement with the simulation and suggest that based on the given power and 10(-3)bit error rate (BER), in comparison with an uncoded system, average communication distance increases 32% with RS code, while 78% with LDPC code.

Screen-camera communication is a new information communication method based on visible light. However, such communication mechanism relies on barcodes to transmit information which suffers a limited capacity and a low communication rate. Hence, we proposed a color multiplexed dynamic QR Code communication system based on mobile devices. Use this method can further improve the communication rates over the system. In our system, a self-defined frame structure has been designed for a better reliability and diversity in the transmission. The experiment results indicated that in the traditional dynamic QR Code transmission mechanism, the real-time communication rate is 150 Kbit/s and the non-real-time communication rate is 300 Kbit/s. While, under the proposed color multiplexed dynamic QR Code communication system, the real-time communication rate can reach 320 Kbit/s and the non-real-time communication rate can reach 900 Kbit/s. After multiple experimental tests, it can transfer text, picture and audio files with no error.

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